• Title of article

    On the numerical investigation of cardiovascular balloon-expandable stent using finite element method

  • Author/Authors

    M. Azaouzi، نويسنده , , M. and Makradi، نويسنده , , A. and Petit، نويسنده , , J. and Belouettar، نويسنده , , S. and Polit، نويسنده , , O.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2013
  • Pages
    10
  • From page
    326
  • To page
    335
  • Abstract
    The present paper shows an effective methodology which is based on Finite Element Analysis (FEA) for the fatigue life prediction (FLP) of a Balloon-Expandable (BE) stent made of stainless steel material (AISI316L). BE stent is a tubular, often mesh-like, structure which is expanded inside a diseased (stenosed) artery segment to restore blood flow and keep the vessel open following angioplasty. With design lives of 10–15 years, fatigue life prediction of these devices is critical for the designer, as fatigue failure may occur after deployment inside the blood vessel due to the heart beating (typically 4 × 107 cycles/year). Therefore, it is crucial to study the effect of stenting conditions and stent design on the fatigue life of BE stents. The objective of this paper is to provide quantitative measures of the stent’s stress amplitude and mean stress which are generated by the cardiac pulse pressure. This allows prediction of the device’s life and optimization of stent designs. In this paper, numerical investigations were conducted using an effective approach based on the well-known stress-based Goodman Diagram (GD) for the FLP of a given stent design. It has been demonstrated that the percentage of artery’s expansion as well as the dimensions of the struts (the fundamental structural unit that forms the stent), have both an impact on the fatigue behavior after stent deployment.
  • Keywords
    Cardiovascular stent , Goodman diagram , Numerical simulation , Finite element analysis , fatigue life prediction
  • Journal title
    Computational Materials Science
  • Serial Year
    2013
  • Journal title
    Computational Materials Science
  • Record number

    1691224